- Improves the table extraction logic in Markdown document parsing.
- Updates SiliconFlow's model list.
- Supports parsing XLS files (Excel97~2003) with improved corresponding error handling.
- Supports Huggingface rerank models.
- Enables relative time expressions ("now", "yesterday", "last week", "next year", and more) in the **Rewrite** agent component.
### Fixed issues
- A repetitive knowledge graph extraction issue.
- Issues with API calling.
- Options in the **Document parser** dropdown are missing.
- A Tavily web search issue.
- Unable to preview diagrams or images in an AI chat.
### Documentation
#### Added documents
[Use tag set](./guides/dataset/use_tag_sets.md)
## v0.17.0
Released on March 3, 2025.
### New features
- AI chat: Implements Deep Research for agentic reasoning. To activate this, enable the **Reasoning** toggle under the **Prompt Engine** tab of your chat assistant dialogue.
- AI chat: Leverages Tavily-based web search to enhance contexts in agentic reasoning. To activate this, enter the correct Tavily API key under the **Assistant Setting** tab of your chat assistant dialogue.
- AI chat: Supports starting a chat without specifying knowledge bases.
- AI chat: HTML files can also be previewed and referenced, in addition to PDF files.
- Dataset: Adds a **Document parser** dropdown menu to dataset configurations. This includes a DeepDoc model option, which is time-consuming, a much faster **naive** option (plain text), which skips DLA (Document Layout Analysis), OCR (Optical Character Recognition), and TSR (Table Structure Recognition) tasks, and several currently *experimental* large model options.
- Agent component: **(x)** or a forward slash `/` can be used to insert available keys (variables) in the system prompt field of the **Generate** or **Template** component.
- Object storage: Supports using Aliyun OSS (Object Storage Service) as a file storage option.
- Models: Updates the supported model list for Tongyi-Qianwen (Qwen), adding DeepSeek-specific models; adds ModelScope as a model provider.
- APIs: Document metadata can be updated through an API.
The following diagram illustrates the workflow of RAGFlow's Deep Research:
- GraphRAG refactor: Knowledge graph is dynamically built on an entire knowledge base (dataset) rather than on an individual file, and automatically updated when a newly uploaded file starts parsing. See [here](https://ragflow.io/docs/dev/construct_knowledge_graph).
- Adds an **Iteration** agent component and a **Research report generator** agent template. See [here](./guides/agent/agent_component_reference/iteration.mdx).
- New UI language: Portuguese.
- Allows setting metadata for a specific file in a knowledge base to enhance AI-powered chats. See [here](./guides/dataset/set_metadata.md).
- Upgrades RAGFlow's document engine [Infinity](https://github.com/infiniflow/infinity) to v0.6.0.dev3.
- Supports GPU acceleration for DeepDoc (see [docker-compose-gpu.yml](https://github.com/infiniflow/ragflow/blob/main/docker/docker-compose-gpu.yml)).
- Supports creating and referencing a **Tag** knowledge base as a key milestone towards bridging the semantic gap between query and response.
:::danger IMPORTANT
The **Tag knowledge base** feature is *unavailable* on the [Infinity](https://github.com/infiniflow/infinity) document engine.
Adds [Infinity's configuration file](https://github.com/infiniflow/ragflow/blob/main/docker/infinity_conf.toml) to facilitate integration and customization of [Infinity](https://github.com/infiniflow/infinity) as a document engine. From this release onwards, updates to Infinity's configuration can be made directly within RAGFlow and will take effect immediately after restarting RAGFlow using `docker compose`. [#3715](https://github.com/infiniflow/ragflow/pull/3715)
### Fixed issues
This release fixes the following issues:
- Unable to display or edit content of a chunk after clicking it.
- A `'Not found'` error in Elasticsearch.
- Chinese text becoming garbled during parsing.
- A compatibility issue with Polars.
- A compatibility issue between Infinity and GraphRAG.
## v0.14.0
Released on November 26, 2024.
### New features
- Supports [Infinity](https://github.com/infiniflow/infinity) or Elasticsearch (default) as document engine for vector storage and full-text indexing. [#2894](https://github.com/infiniflow/ragflow/pull/2894)
- Enhances user experience by adding more variables to the Agent and implementing auto-saving.
- Adds a three-step translation agent template, inspired by [Andrew Ng's translation agent](https://github.com/andrewyng/translation-agent).
- Adds an SEO-optimized blog writing agent template.
- Provides HTTP and Python APIs for conversing with an agent.
- Supports the use of English synonyms during retrieval processes.
- Optimizes term weight calculations, reducing the retrieval time by 50%.
- Improves task executor monitoring with additional performance indicators.
- Replaces Redis with Valkey.
- Adds three new UI languages (*contributed by the community*): Indonesian, Spanish, and Vietnamese.
### Compatibility changes
As of this release, **service_config.yaml.template** replaces **service_config.yaml** for configuring backend services. Upon Docker container startup, the environment variables defined in this template file are automatically populated and a **service_config.yaml** is auto-generated from it. [#3341](https://github.com/infiniflow/ragflow/pull/3341)
This approach eliminates the need to manually update **service_config.yaml** after making changes to **.env**, facilitating dynamic environment configurations.
:::danger IMPORTANT
Ensure that you [upgrade **both** your code **and** Docker image to this release](https://ragflow.io/docs/dev/upgrade_ragflow#upgrade-ragflow-to-the-most-recent-officially-published-release) before trying this new approach.
:::
### Related APIs
#### HTTP APIs
- [Create session with agent](https://ragflow.io/docs/dev/http_api_reference#create-session-with-agent)
- [Converse with agent](https://ragflow.io/docs/dev/http_api_reference#converse-with-agent)
#### Python APIs
- [Create session with agent](https://ragflow.io/docs/dev/python_api_reference#create-session-with-agent)
- [Converse with agent](https://ragflow.io/docs/dev/python_api_reference#create-session-with-agent)
- Offers slim editions of RAGFlow's Docker images, which do not include built-in BGE/BCE embedding or reranking models.
- Improves the results of multi-round dialogues.
- Enables users to remove added LLM vendors.
- Adds support for **OpenTTS** and **SparkTTS** models.
- Implements an **Excel to HTML** toggle in the **General** chunk method, allowing users to parse a spreadsheet into either HTML tables or key-value pairs by row.
- Adds agent tools **YahooFinance** and **Jin10**.
- Adds an investment advisor agent template.
### Compatibility changes
As of this release, RAGFlow offers slim editions of its Docker images to improve the experience for users with limited Internet access. A slim edition of RAGFlow's Docker image does not include built-in BGE/BCE embedding models and has a size of about 1GB; a full edition of RAGFlow is approximately 9GB and includes both built-in embedding models and embedding models that will be downloaded once you select them in the RAGFlow UI.
The default Docker image edition is `nightly-slim`. The following list clarifies the differences between various editions:
-`nightly-slim`: The slim edition of the most recent tested Docker image.
-`v0.12.0-slim`: The slim edition of the most recent **officially released** Docker image.
-`nightly`: The full edition of the most recent tested Docker image.
-`v0.12.0`: The full edition of the most recent **officially released** Docker image.
See [Upgrade RAGFlow](https://ragflow.io/docs/dev/upgrade_ragflow) for instructions on upgrading.
- Introduces a text-to-SQL template in the Agent UI.
- Implements Agent APIs.
- Incorporates monitoring for the task executor.
- Introduces Agent tools **GitHub**, **DeepL**, **BaiduFanyi**, **QWeather**, and **GoogleScholar**.
- Supports chunking of EML files.
- Supports more LLMs or model services: **GPT-4o-mini**, **PerfXCloud**, **TogetherAI**, **Upstage**, **Novita.AI**, **01.AI**, **SiliconFlow**, **PPIO**, **XunFei Spark**, **Baidu Yiyan**, and **Tencent Hunyuan**.
## v0.9.0
Released on August 6, 2024.
### New features
- Supports GraphRAG as a chunk method.
- Introduces Agent component **Keyword** and search tools, including **Baidu**, **DuckDuckGo**, **PubMed**, **Wikipedia**, **Bing**, and **Google**.
- Supports speech-to-text recognition for audio files.
- Supports model vendors **Gemini** and **Groq**.
- Supports inference frameworks, engines, and services including **LM studio**, **OpenRouter**, **LocalAI**, and **Nvidia API**.
- Supports using reranker models in Xinference.
## v0.8.0
Released on July 8, 2024.
### New features
- Supports Agentic RAG, enabling graph-based workflow construction for RAG and agents.
- Supports model vendors **Mistral**, **MiniMax**, **Bedrock**, and **Azure OpenAI**.
- Supports DOCX files in the MANUAL chunk method.
- Supports DOCX, MD, and PDF files in the Q&A chunk method.
## v0.7.0
Released on May 31, 2024.
### New features
- Supports the use of reranker models.
- Integrates reranker and embedding models: [BCE](https://github.com/netease-youdao/BCEmbedding), [BGE](https://github.com/FlagOpen/FlagEmbedding), and [Jina](https://jina.ai/embeddings/).
- Supports LLMs Baichuan and VolcanoArk.
- Implements [RAPTOR](https://arxiv.org/html/2401.18059v1) for improved text retrieval.
- Supports HTML files in the GENERAL chunk method.
- Provides HTTP and Python APIs for deleting documents by ID.
- Supports ARM64 platforms.
:::danger IMPORTANT
While we also test RAGFlow on ARM64 platforms, we do not maintain RAGFlow Docker images for ARM.